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- W2064963984 abstract "Abstract An Image Randomness Test (IRT) is applied to obtain efficient object estimates in inverse problems, specifically, in the image restoration. According to the IRT, an observed image can be considered as one of the typical random image simulations for a feasible object estimate. The likelihood is not a comprehensive estimate from the IRT point of view; in addition, the Maximum Likelihood principle contradicts the IRT. A Mean Likelihood requirement is proposed for this purpose together with the statistical independence test. A connection of the concepts introduced with the information theory by Shannon is shown. The limiting accuracy and resolution are discussed for simple observational conditions. Numerical simulations show that the stability of the inverse solution for the method described is significantly increased. Exact and asymptotic expressions for the information and entropy of a Poisson random variable are given in Appendices, as well as some examples of the parameter estimation with the mea..." @default.
- W2064963984 created "2016-06-24" @default.
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- W2064963984 date "1995-01-01" @default.
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- W2064963984 title "The image randomness test for inverse problems" @default.
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- W2064963984 doi "https://doi.org/10.1080/10556799508232058" @default.
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